diff --git a/privacy/analysis/compute_dp_sgd_privacy.py b/privacy/analysis/compute_dp_sgd_privacy.py
index 4ca2ab1..e4bab4d 100644
--- a/privacy/analysis/compute_dp_sgd_privacy.py
+++ b/privacy/analysis/compute_dp_sgd_privacy.py
@@ -61,6 +61,10 @@ flags.mark_flag_as_required('epochs')
 def apply_dp_sgd_analysis(q, sigma, steps, orders, delta):
   """Compute and print results of DP-SGD analysis."""
 
+  # compute_rdp requires that sigma be the ratio of the standard deviation of
+  # the Gaussian noise to the l2-sensitivity of the function to which it is
+  # added. Hence, sigma here corresponds to the `noise_multiplier` parameter
+  # in the DP-SGD implementation found in privacy.optimizers.dp_optimizer
   rdp = compute_rdp(q, sigma, steps, orders)
 
   eps, _, opt_order = get_privacy_spent(orders, rdp, target_delta=delta)
@@ -80,13 +84,10 @@ def main(argv):
   del argv  # argv is not used.
 
   q = FLAGS.batch_size / FLAGS.N  # q - the sampling ratio.
-
   if q > 1:
     raise app.UsageError('N must be larger than the batch size.')
-
   orders = ([1.25, 1.5, 1.75, 2., 2.25, 2.5, 3., 3.5, 4., 4.5] +
             list(range(5, 64)) + [128, 256, 512])
-
   steps = int(math.ceil(FLAGS.epochs * FLAGS.N / FLAGS.batch_size))
 
   apply_dp_sgd_analysis(q, FLAGS.noise_multiplier, steps, orders, FLAGS.delta)